US2019156438A1PendingUtilityA1
Energy and production optimization system for factory to grid integration
Est. expiryNov 13, 2035(~9.3 yrs left)· nominal 20-yr term from priority
G06Q 30/0202G06Q 50/06G05B 13/047G06Q 30/0206H02J 13/0006G06Q 10/06312Y02B90/20Y04S20/00Y02E40/70Y04S10/50
49
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Claims
Abstract
Production tasks are scheduled to optimize production constraints while taking time varying energy prices into account. An energy management layer (EML) is in communication with a manufacturing domain as well as a smart grid domain. The EML receives information relating to a factory workflow, costs associated with operating units within the factory, and static utility information such as tariff models and incentives. Time variant energy price information is obtained from a utility regarding periodic price levels for a near future timeframe. The workflow is converted to a matrix representation that is acceptable to a mixed integer linear programming (MILP) solver. An algebraic factor representing a tradeoff between energy cost and full-capacity production is minimized to produce production variables which control production and limit production units and tasks to be performed during time slots that are most economically favorable.
Claims
exact text as granted — not AI-modified1 . A method of integrating manufacturing processing and energy delivery costs optimization in a factory comprising the steps of:
establishing an energy management layer in communication with an energy domain containing a smart grid and a manufacturing domain containing a manufacturing execution system, the energy management layer comprising:
a data logger for capturing state information of the factory;
an interface between the energy management layer and a controller in the factory;
a web server for receiving information relating to the energy delivery costs;
a data store for storing the state information and the energy delivery costs; and
an optimization engine in communication with the data store to perform calculations on integrated factory state data and energy delivery cost data;
receiving information relating to the operation of production units to the energy management layer via the interface in the data store; receiving information relating to time varying energy prices via the web server in the data store; optimizing in the optimization engine within the energy management layer, a production schedule for performance of at least one task by at least one production unit within a time window that is optimized based at least in part on the information relating to the time varying energy prices.
2 . The method of claim 1 , wherein providing information relating to the operation of production units comprises:
providing information relating to a workflow of the factory; providing information relating to a cost of operation of the at least one production unit; providing information relating to at least one of a tariff model and energy cost incentives provided by a utility.
3 . The method of claim 2 , wherein providing information relating to time varying prices of energy comprises:
obtaining a periodic schedule of energy prices from a utility, wherein the periodic schedule of energy prices reflects a unit cost of energy for a pre-determined time period within a near future timeframe.
4 . The method of claim 3 , wherein obtaining a periodic schedule of energy prices comprises:
accessing a public data store of the utility; and retrieving from the data store a schedule of prices providing a unit energy price for a given hour in a day following the day on which the schedule of prices was retrieved.
5 . The method of claim 2 , wherein the workflow of the factory is provided as a State-Task Network (STN).
6 . The method of claim 2 , wherein the workflow of the factory is provided as a Resource-Task Network (RTN).
7 . The method of claim 2 , wherein providing information to a cost of operation of the at least one production unit comprises:
providing an energy cost incurred by activating a production unit to perform a given task.
8 . The method of claim 1 , wherein providing information relating to time varying prices of energy comprises:
obtaining a periodic schedule of energy prices from a utility, wherein the periodic schedule of energy prices reflects a unit cost of energy for a pre-determined time period within a near future timeframe.
9 . The method of claim 8 , wherein obtaining a periodic schedule of energy prices comprises:
accessing a public data store of the utility; and retrieving from the data store a schedule of prices providing a unit energy price for a given hour in a day following the day on which the schedule of prices was retrieved.
10 . The method of claim 1 , wherein the energy management layer is in communication with the energy domain via a distributed network.
11 . The method of claim 10 , wherein the distributed network is the Internet.
12 . The method of claim 1 wherein optimizing a production schedule for performance of the at least one task by at least one production unit comprises:
determining a power quote for each time slot of a plurality of time slots within a given timeframe;
determining an energy cost for each of the time slots in the plurality of time slots;
scheduling the at least one task in time slots in which the determined energy cost is minimized while meeting a power quote constraint for the scheduled time slots.
13 . The method of claim 1 , further comprising the steps of:
defining a scheduling parameter according to:
W
ijt
∈
{
0
,
1
}
,
∑
i
∈
I
j
W
ijt
≤
1
,
∀
j
∈
J
,
t
∈
T
,
where I j is a set of tasks that may be performed in unit j; and
W ijt is a set of binary values wherein a value of 1 represents that a task I starts at unit j at a beginning of a time interval t.
14 . The method of claim 13 , further comprising the step of:
defining a total energy bill C, according to:
C
=
∑
i
∈
T
∑
i
∈
I
j
C
j
W
ijt
.
15 . The method of claim 14 , further comprising the step of:
defining a utility ratio representative of the factory's productivity according to:
R
=
∑
t
∈
T
∑
j
∈
N
∑
i
∈
I
j
W
ijt
∑
t
∈
T
∑
i
∈
T
∑
i
∈
I
j
1
.
16 . The method of claim 15 , wherein R is a value between zero and one, a value of one representing 100% utilization on all units J.
17 . The method of claim 13 , wherein the optimizing step further comprises:
optimizing the value of J, according to:
min J=αC +(1−α)(1− R ),α∈[0,1].
18 . The method of claim 17 , wherein optimizing the value of J is subject to:
∑
i
∈
I
j
W
ijt
≤
1
,
∀
j
∈
J
,
t
∈
T
,
W
ijt
∈
{
0
,
1
}
,
∑
i
∈
I
j
C
j
W
ijt
≤
Q
t
,
∀
j
∈
J
,
t
∈
T
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